Today, machines (also referred to herein as “assets”) are ubiquitous in many industries. From locomotives that transfer cargo across countries to farming equipment that harvest crops, assets play an important role in everyday life. Depending on the role that an asset serves, its complexity, and cost, may vary. For instance, some assets include multiple subsystems that must operate in harmony for the asset to function properly (e.g., an engine, transmission, etc.).
Because of the increasing role that assets play, it is also becoming increasingly desirable to monitor and analyze assets in operation. To facilitate this, some have developed mechanisms to monitor asset attributes and detect abnormal conditions at an asset. For instance, one approach for monitoring assets generally involves various sensors and/or actuators distributed throughout an asset that monitor the operating conditions of the asset and provide signals reflecting the asset's operation to an on-asset computer. As one representative example, if the asset is a locomotive, the sensors and/or actuators may monitor parameters such as temperatures, pressures, fluid levels, voltages, and/or speeds, among other examples. If the signals output by one or more of the sensors and/or actuators reach certain values, the on-asset computer may then generate an abnormal condition indicator, such as a “fault code,” which is an indication that an abnormal condition has occurred within the asset. The on-asset computer may also be configured to monitor for, detect, and generate data indicating other events that may occur at the asset, such as asset shutdowns, restarts, etc.
The on-asset computer may also be configured to send data reflecting the attributes of the asset, including operating data such as signal data, abnormal-condition indicators, and/or asset event indicators, to a remote location for further analysis.